Iterative Linear Interpolation Based on Fuzzy Gradient Model for Low-Cost VLSI Implementation

Chen, Chao‐Lieh; Lai, Chin-Wei

doi:10.1109/tvlsi.2013.2276410

Cited by 13 publications

(4 citation statements)

References 12 publications

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“…Much work has been published on function approximation and evaluation, some of the more recent being [35][36][37]. It should be noted that the methods presented in this paper can be applied to most, if not all other designs for function approximation.…”

Section: Future Workmentioning

confidence: 99%

Linear and Quadratic Interpolators Using Truncated-Matrix Multipliers and Squarers

Walters

2015

Computers

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This paper presents a technique for designing linear and quadratic interpolators for function approximation using truncated multipliers and squarers. Initial coefficient values are found using a Chebyshev-series approximation and then adjusted through exhaustive simulation to minimize the maximum absolute error of the interpolator output. This technique is suitable for any function and any precision up to 24 bits (IEEE single precision). Designs for linear and quadratic interpolators that implement the 1/x, 1/ √ x, log 2 (1 + 2 x ), log 2 (x) and 2 x functions are presented and analyzed as examples. Results show that a proposed 24-bit interpolator computing 1/x with a design specification of ±1 unit in the last place of the product (ulp) error uses 16.4% less area and 15.3% less power than a comparable standard interpolator with the same error specification. Sixteen-bit linear interpolators for other functions are shown to use up to 17.3% less area and 12.1% less power, and 16-bit quadratic interpolators are shown to use up to 25.8% less area and 24.7% less power.

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Section: Future Workmentioning

confidence: 99%

Linear and Quadratic Interpolators Using Truncated-Matrix Multipliers and Squarers

Walters

2015

Computers

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“…However, algorithm complexity is higher, calculation amount is larger, and real-time processing is difficult 10 . Chen proposed a low-cost linear interpolation method and compared the differences of various interpolation methods implemented on a chip 11 . Filtering for large windows also results in more consumption of logic resources, and filter weights must still be given through LUT.…”

Section: Introductionmentioning

confidence: 99%

Real-time image distortion correction based on FPGA

Ai²,

Hu³

et al. 2022

Fourteenth International Conference on Digital Image Processing (ICDIP 2022)

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As the primary method for real-time image processing, a field-programmable gate array (FPGA) is widely used in binocular vision systems. Distortion correction is an important component of binocular stereo vision systems. When implementing a real-time image distortion correction algorithm on FPGA, problems, such as insufficient on-chip storage space and high complexity of coordinate correction calculation methods, occur. These problems are analyzed in detail in this study. On the basis of the reverse mapping method, a distortion correction algorithm that uses a lookup table (LUT) is proposed. A compression with restoration method is established for this LUT to reduce space occupation. The corresponding cache method of LUT and the image data are designed. The algorithm is verified on our binocular stereo vision system based on Xilinx Zynq-7020. The experiments show that the proposed algorithm can achieve real-time and high precision gray image distortion correction effect and significantly reduce the consumption of on-chip resources. Enough to meet the requirements of accurate binocular stereo vision system.

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“…Therefore, many researchers have been using interpolation methods to analyze data of different applications. Some of the interpolation methods are as following: B-spline interpolation using linear approximations for setting up viewing and projection matrices and describing complex objects were studied in reference [1], implementing a cubic spline interpolation algorithm on DSP was studied in reference [2], an iterative linear interpolation based on fuzzy gradient model for low-cost VLSI implementation was introduced by reference [3], a polynomial interpolation for space-efficient verifiable secret sharing was given in reference [4], an interpolation method to investigate the improvement in image quality for ground penetrating radar (GPR) acquisition was highlighted in reference [5], gauss interpolation algorithms for nonlinear rational parameters were presented in reference [6], four image interpolation methods for 2-D AR modeling were given in reference [7], a polynomial approach to evaluate the fragmented function approach for two secure two-party computation (STPC) was introduced in reference [8], a bivariate splines in piecewise constant tension as the solution for a functional minimization problem was given in reference [9], a cubic spline interpolation algorithm for smoothness interpolation model of non-circular curve mechanical mold was studied in reference [10], a spline interpolation functions for solution of a non-linear equation was given in reference [11], a view interpolation method from defocused stereo images using linear filtering was introduced in reference [12], a linear interpolation effects on signal transferring was highlighted in reference [13], a novel and fast cubic B-splines algorithm for cancellation of random valued impulse noise was given in reference [14], a real time implementation of cubic B-spline algorithm for electro optical tracking system was studied in reference [15], a cubic B-spline curves based research of the approximate algorithm was given in reference [16], and a fast algorithm for quadratic and cubic spline wavelets was provided in reference [17]. Among these, the spline curve makes it easy to build an interface that will allow designing and controlling the shape of complex curves and surfaces by using low-degree polynomials in each of the intervals and by choosing the polynomial pieces such that they fit smoothly together.…”

Section: Introductionmentioning

confidence: 99%

Untitled

2019

Adv. Electr. Comp. Eng.

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Peak detection of any time serial signals can be done using different methods. However, exact positions of the peaks cannot be achieved, if the method does not have a high sensitivity detection capability. It is known that various errors appear between the real peak value and the measured value; therefore, a true peak value can be obtained from the measured value by using a highly sensitive detection method. For this reason, spline interpolation is used to estimate the peak points from measured values. In this paper, highly sensitive peak detection of high-frequency signals based on FPGA is proposed using spline algorithm, which is capable of calculating the middle points using the first and last points on the signal. To evaluate the system, the histograms, the mean, and the variance of the peak values before and after spline interpolation are compared. Simulation results show that calculated peak points using splines and real peak values of a signal are very close to each other since the spline algorithm has very high calculation sensitivity. In addition, spline results show us how much error the existing peak values have.

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Iterative Linear Interpolation Based on Fuzzy Gradient Model for Low-Cost VLSI Implementation

Cited by 13 publications

References 12 publications

Linear and Quadratic Interpolators Using Truncated-Matrix Multipliers and Squarers

Linear and Quadratic Interpolators Using Truncated-Matrix Multipliers and Squarers

Real-time image distortion correction based on FPGA

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